A non-invasive wearable microwave sensor for Alzheimer's Stage differentiation using realistic 3D human head phantoms - Jinan N. Shehab; Malik Jasim Farhan; Saad Al-Azawi (Results in Engineering)
This study presents an advanced, safe, low-cost, and non-invasive sensor system for the early detection and monitoring of Alzheimer's disease, making it a promising complementary tool to conventional methods such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET). The system relies on the development and fabrication of four six-layer realistic 3D human head models for use in a microwave brain imaging system, along with a small sensor dedicated to disease detection. These phantoms were designed to accurately mimic human brain tissue, with each layer having distinct electrical properties and varying thicknesses. Three phantoms were designed to mimic different Alzheimer's disease stages. The stage classification was based on medical research, with the disease initially occurring in the hippocampus before spreading to the rest of the brain. Changes associated with disease progression were also considered, such as shrinkage of gray and white matter and increased cerebrospinal fluid (CSF) penetration. Each prototype was tested using the proposed sensor, assessing its accuracy in distinguishing between different phases based on the signal reflected from the head and the changes in return losses. The sensor dimension of 32 × 37 × 0.36 mm³, and it operates at 3.241 GHz in simulations and 3.62 GHz in experiments. The sensor features a bandwidth of 1.4 GHz, a gain of 1.56 dB, and a specific absorption ratio of 0.566, enhancing its ability to penetrate deep into brain tissue. The proposed system features a compact antenna design that achieves an optimal balance between gain and size, along with a realistic head phantom that enhances testing accuracy.While not yet validated for clinical deployment, its performance was evaluated using a vector network analyzer (VNA), and the results confirmed its high compatibility with biological tissues, demonstrating its effectiveness in accurately detecting Alzheimer's-related dielectric changes through microwave technology.